1. Field
The invention disclosed herein relates to neural networks, and in particular, to techniques for using a neural network to perform image signal processing.
2. Description of the Related Art
The wide availability of imaging sensors has permitted manufacturers to include imaging capabilities in many devices. For example, it is hard to find a cellular telephone that does not include a digital camera. While the manufacturing costs for imaging sensors have been greatly reduced, and the technology for imaging has greatly improved, image signal processing remains a challenge.
Typically, image signal processing has required dedicated components configured for a particular imaging sensor. Development of a specialized image signal processor can be very costly. For example, a substantial amount of computer code must be written for processing images. Writing such code involves a lot of expertise to perform design and tuning of the processing. Further, such code must be tailored to individual sensors, and may need to be customized for a given user. To complicate matters further, such code does not account for manufacturing variability in a group of imaging sensors as may arise in the manufacturing process.
Aside from increased manufacturing cost and complexity, a given chipset dedicated to image signal processing can be relatively inflexible and not well suited to all environments. Accordingly, the greater the image signal processing capability included in an imaging device, the greater the associated cost and space required within the device.
What are needed are improved techniques for more effectively providing image signal processing. The techniques should make use of common resources such as a multipurpose processor and memory. Preferably, the techniques should be highly flexible such that they may be easily improved upon.